Clicker Questions

to go along with

Modern Data Science with R, 3rd edition by Baumer, Kaplan, and Horton

Introduction to Statistical Learning with Applications in R by James, Witten, Hastie, and Tibshirani


  1. The reason to take random samples is:1
    1. to make cause and effect conclusions
    2. to get as many variables as possible
    3. it’s easier to collect a large dataset
    4. so that the data are a good representation of the population
    5. I have no idea why one would take a random sample

  1. The reason to allocate/assign explanatory variables is:2
    1. to make cause and effect conclusions
    2. to get as many variables as possible
    3. it’s easier to collect a large dataset
    4. so that the data are a good representation of the population
    5. I have no idea what you mean by “allocate/assign” (or “explanatory variable” for that matter)

  1. Approximately how big is a tweet?3
    1. 0.01Kb
    2. 0.1Kb
    3. 1Kb
    4. 100Kb
    5. 1000Kb = 1Mb

  1. \(R^2\) measures:4
    1. the proportion of variability in vote margin as explained by tweet share.
    2. the proportion of variability in tweet share as explained by vote margin.
    3. how appropriate the linear part of the linear model is.
    4. whether or not particular variables should be included in the model.

  1. R / R Studio / Quarto5
    1. all good
    2. started, progress is slow and steady
    3. started, very stuck
    4. haven’t started yet
    5. what do you mean by “R”?

  1. Git / GitHub6
    1. all good
    2. started, progress is slow and steady
    3. started, very stuck
    4. haven’t started yet
    5. what do you mean by “Git”?

  1. Which of the following includes talking to the remote version of GitHub?7
    1. changing your name (updating the YAML)
    2. committing the file(s)
    3. pushing the file(s)
    4. some of the above
    5. all of the above

  1. What is the error?8
    1. poor assignment operator
    2. unmatched quotes
    3. improper syntax for function argument
    4. invalid object name
    5. no mistake
shup2 <-- "Hello to you!"

  1. What is the error?9
    1. poor assignment operator
    2. unmatched quotes
    3. improper syntax for function argument
    4. invalid object name
    5. no mistake
3shup <-  "Hello to you!"

  1. What is the error?10
    1. poor assignment operator
    2. unmatched quotes
    3. improper syntax for function argument
    4. invalid object name
    5. no mistake
shup4 <-  "Hello to you!

  1. What is the error?11
    1. poor assignment operator
    2. unmatched quotes
    3. improper syntax for function argument
    4. invalid object name
    5. no mistake
shup5 <-  date()

  1. What is the error?12
    1. poor assignment operator
    2. unmatched quotes
    3. improper syntax for function argument
    4. invalid object name
    5. no mistake
shup6 <-  sqrt 10

  1. Do you keep a calendar / schedule / planner?13
    1. Yes
    2. No

  1. Do you keep a calendar / schedule / planner? If you answered “Yes” …14
    1. Yes, on Google Calendar
    2. Yes, on Calendar for macOS
    3. Yes, on Outlook for Windows
    4. Yes, in some other app
    5. Yes, by hand

  1. The goal of making a figure is…15
    1. To draw attention to your work.
    2. To facilitate comparisons.
    3. To provide as much information as possible.

  1. A good reason to make a particular choice of a graph is:16
    1. Because the journal / field has particular expectations for how the data are presented.
    2. Because some variables naturally fit better on some graphs (e.g., numbers on scatter plots).
    3. Because that graphic displays the message you want as optimally as possible.

  1. Why are the points orange?17
    1. R translates “navy” into orange.
    2. color must be specified in geom_point()
    3. color must be specified outside the aes() function
    4. the default plot color is orange

ggplot(data = Births78, 
       aes(x = date, y = births, color = "navy")) + 
  geom_point() +          
  ggtitle("US Births in 1978")

  1. Why are the dots blue and the lines colored?18
    1. dot color is given as “navy”, line color is given as wday.
    2. both colors are specified in the ggplot() function.
    3. dot coloring takes precedence over line coloring.
    4. line coloring takes precedence over dot coloring.


  1. Setting vs. Mapping. If I want information to be passed to all data points (not variable):19
    1. map the information inside the aes() function.
    2. set the information outside the aes() function

  1. The Snow figure was most successful at:20
    1. making the data stand out
    2. facilitating comparison
    3. putting the work in context
    4. simplifying the story

  1. The Challenger figure(s) was(were) least successful at:21
    1. making the data stand out
    2. facilitating comparison
    3. putting the work in context
    4. simplifying the story

  1. The biggest difference between Snow and the Challenger was:22
    1. The amount of information portrayed.
    2. One was better at displaying cause.
    3. One showed the relevant comparison better.
    4. One was more artistic.

  1. Caffeine and Calories. What was the biggest concern over the average value axes?23
    1. It isn’t at the origin.
    2. They should have used all the data possible to find averages.
    3. There wasn’t a random sample.
    4. There wasn’t a label explaining why the axes were where they were.

:::

Footnotes

    1. so that the data are a good representation of the population
    ↩︎
    1. to make cause and effect conclusions
    ↩︎
    1. about 0.1Kb. Turns out that 3.5 billion tweets * 0.1Kb = 350Gb (0.35 Tb). My laptop is pretty good, and it has 36 Gb of memory (RAM) and 4 Tb of storage. It would not be able to work with 3.5 billion tweets.
    ↩︎
    1. the proportion of variability in vote margin as explained by tweet share.
    ↩︎
  1. wherever you are, make sure you are communicating with me when you have questions!↩︎

  2. wherever you are, make sure you are communicating with me when you have questions!↩︎

    1. pushing the file(s)
    ↩︎
    1. poor assignment operator
    ↩︎
    1. invalid object name
    ↩︎
    1. unmatched quotes
    ↩︎
    1. no mistake
    ↩︎
    1. improper syntax for a function argument
    ↩︎
    1. I mean, the right answer has to be Yes, right!??!
    ↩︎
  3. no right answer here!↩︎

  4. Yes! All the responses are reasons to make a figure.↩︎

    1. Because that graphic displays the message you want as optimally as possible.
    ↩︎
    1. color must be specified outside the aes() function
    ↩︎
    1. dot color is specified as “navy”, line color is specified as wday.
    ↩︎
    1. set the information outside the aes() function
    ↩︎
  5. answers may vary. I’d say c. putting the work in context. Others might say b. facilitating comparison or d. simplifying the story. However, I don’t think a correct answer is a. making the data stand out.↩︎

    1. making the data stand out
    ↩︎
    1. One showed the relevant comparison better.
    ↩︎
    1. It isn’t at the origin. in combination with d. There wasn’t a label explaining why the axes were where they were. The story associated with the average value axes is not clear to the reader.
    ↩︎

Reuse